Quality of an Ontology as a Dynamic Optimisation Problem. - Michael Cochez; Vagan Y. Terziyan (ICTERI, 2012)

The Use of Distributed Version Control Systems in Advanced Programming Courses. - Michael Cochez; Ville Isomöttönen; Ville Tirronen; Jonne Itkonen (ICTERI, 2013)

How Do Computer Science Students Use Distributed Version Control Systems? - Michael Cochez; Ville Isomöttönen; Ville Tirronen; Jonne Itkonen (ICTERI (Revised Selected Papers), 2013)

Issues with a course that emphasizes self-direction. - Ville Isomöttönen; Ville Tirronen; Michael Cochez (ITiCSE, 2013)

Challenges and Confusions in Learning Version Control with Git. - Ville Isomöttönen; Michael Cochez (ICTERI, 2014)

Locality-Sensitive Hashing for Massive String-Based Ontology Matching. - Michael Cochez (WI-IAT (2), 2014)

Balanced Large Scale Knowledge Matching Using LSH Forest. - Michael Cochez; Vagan Y. Terziyan; Vadim Ermolayev (International KEYSTONE Conference, 2015)

Twister Tries: Approximate Hierarchical Agglomerative Clustering for Average Distance in Linear Time. - Michael Cochez; Hao Mou (SIGMOD Conference, 2015)

Scalable Hierarchical Clustering: Twister Tries with a Posteriori Trie Elimination. - Michael Cochez; Ferrante Neri (SSCI, 2015)

Anomaly Detection Algorithms for the Sleeping Cell Detection in LTE Networks. - Sergey Chernov 003; Michael Cochez; Tapani Ristaniemi (VTC Spring, 2015)

TB-Structure: Collective Intelligence for Exploratory Keyword Search. - Vagan Y. Terziyan; Mariia Golovianko; Michael Cochez (International KEYSTONE Conference, 2016)

Using Distributional Semantics for Automatic Taxonomy Induction. - Bushra Zafar; Michael Cochez; Usman Qamar (FIT, 2016)

Knowledge Representation on the Web Revisited: The Case for Prototypes. - Michael Cochez; Stefan Decker; Eric Prud'hommeaux (ISWC (1), 2016)

Knowledge Representation on the Web revisited: Tools for Prototype Based Ontologies. - Michael Cochez; Stefan Decker; Eric Prud'hommeaux (CoRR, 2016)

The Future of the Semantic Web: Prototypes on a Global Distributed Filesystem. - Michael Cochez; Dominik Hüser; Stefan Decker (ICDCS, 2017)

Global RDF Vector Space Embeddings. - Michael Cochez; Petar Ristoski; Simone Paolo Ponzetto; Heiko Paulheim (ISWC (1), 2017)

Towards a FAIR Sharing of Scientific Experiments: Improving Discoverability and Reusability of Dielectric Measurements of Biological Tissues. - Md. Rezaul Karim 001; Matthias Heinrichs; Lars Christoph Gleim; Michael Cochez; Emily Porter; Alessandra La Gioia; Saqib Salahuddin; Stefan Decker; Martin O'Halloran; Oya Beyan (SWAT4LS, 2017)

Biased graph walks for RDF graph embeddings. - Michael Cochez; Petar Ristoski; Simone Paolo Ponzetto; Heiko Paulheim (WIMS, 2017)

Large Scale Knowledge Matching with Balanced Efficiency-Effectiveness Using LSH Forest. - Michael Cochez; Vagan Y. Terziyan; Vadim Ermolayev (Trans. Comput. Collect. Intell., 2017)

A First Experiment on Including Text Literals in KGloVe. - Michael Cochez; Martina Garofalo; Jérôme Lenßen; Maria Angela Pellegrino (Semdeep/NLIWoD@ISWC, 2018)

Measuring Semantic Coherence of a Conversation. - Svitlana Vakulenko; Maarten de Rijke; Michael Cochez; Vadim Savenkov; Axel Polleres (ISWC (1), 2018)

Where to Park?: Predicting Free Parking Spots in Unmonitored City Areas. - Andrei Ionita; André Pomp; Michael Cochez; Tobias Meisen; Stefan Decker (WIMS, 2018)

BigNet 2018 Chairs' Welcome & Organization. - Jie Tang 001; Michalis Vazirgiannis; Yuxiao Dong; Fragkiskos D. Malliaros; Michael Cochez; Mayank Kejriwal; Achim Rettinger (WWW (Companion Volume), 2018)

On the computation of Shannon Entropy from Counting Bloom Filters. - Michael Cochez (CoRR, 2018)

Recurrent Deep Embedding Networks for Genotype Clustering and Ethnicity Prediction. - Md. Rezaul Karim 001; Michael Cochez; Oya Beyan; Achille Zappa; Ratnesh Sahay; Stefan Decker; Dietrich Rebholz-Schuhmann (CoRR, 2018)

Leveraging Knowledge Graph Embedding Techniques for Industry 4.0 Use Cases. - Martina Garofalo; Maria Angela Pellegrino; Abdulrahman Altabba; Michael Cochez (CoRR, 2018)

Mining maximal frequent patterns in transactional databases and dynamic data streams: A spark-based approach. - Md. Rezaul Karim 001; Michael Cochez; Oya Deniz Beyan; Chowdhury Farhan Ahmed; Stefan Decker (Inf. Sci., 2018)

Drug-Drug Interaction Prediction Based on Knowledge Graph Embeddings and Convolutional-LSTM Network. - Md. Rezaul Karim 001; Michael Cochez; Joao Bosco Jares; Mamtaz Uddin; Oya Beyan; Stefan Decker (BCB, 2019)

OncoNetExplainer: Explainable Predictions of Cancer Types Based on Gene Expression Data. - Md. Rezaul Karim 001; Michael Cochez; Oya Beyan; Stefan Decker; Christoph Lange 002 (BIBE, 2019)

Message Passing for Complex Question Answering over Knowledge Graphs. - Svitlana Vakulenko; Javier David Fernandez Garcia; Axel Polleres; Maarten de Rijke; Michael Cochez (CIKM, 2019)

Leveraging Knowledge Graph Embeddings for Natural Language Question Answering. - Ruijie Wang 003; Meng Wang 009; Jun Liu 002; Weitong Chen 001; Michael Cochez; Stefan Decker (DASFAA (1), 2019)

A Configurable Evaluation Framework for Node Embedding Techniques. - Maria Angela Pellegrino; Michael Cochez; Martina Garofalo; Petar Ristoski (ESWC (Satellite Events), 2019)

Linked Open Data Validity - A Technical Report from ISWS 2018. - Tayeb Abderrahmani Ghor; Esha Agrawal; Mehwish Alam; Omar Alqawasmeh; Claudia d'Amato; Amina Annane; Amr Azzam; Andrew Berezovskyi; Russa Biswas; Mathias Bonduel; Quentin Brabant; Cristina-Iulia Bucur; et al. (CoRR, 2019)

Privacy Attacks on Network Embeddings. - Michael Ellers; Michael Cochez; Tobias Schumacher 002; Markus Strohmaier; Florian Lemmerich (CoRR, 2019)

Transferring Knowledge from Monitored to Unmonitored Areas for Forecasting Parking Spaces. - Andrei Ionita; André Pomp; Michael Cochez; Tobias Meisen; Stefan Decker (Int. J. Artif. Intell. Tools, 2019)

DeepCOVIDExplainer: Explainable COVID-19 Diagnosis from Chest X-ray Images. - Md. Rezaul Karim 001; Till Döhmen; Michael Cochez; Oya Beyan; Dietrich Rebholz-Schuhmann; Stefan Decker (BIBM, 2020)

Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network. - Md. Rezaul Karim 001; Bharathi Raja Chakravarthi; John P. McCrae; Michael Cochez (DSAA, 2020)

SchemaTree: Maximum-Likelihood Property Recommendation for Wikidata. - Lars Christoph Gleim; Rafael Schimassek; Dominik Hüser; Maximilian Peters; Christoph Krämer; Michael Cochez; Stefan Decker (ESWC, 2020)

GEval: A Modular and Extensible Evaluation Framework for Graph Embedding Techniques. - Maria Angela Pellegrino; Abdulrahman Altabba; Martina Garofalo; Petar Ristoski; Michael Cochez (ESWC, 2020)

Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification. - Ruud van Bakel; Teodor Aleksiev; Daniel Daza; Dimitrios Alivanistos; Michael Cochez (GKR, 2020)

Message Passing for Query Answering over Knowledge Graphs. - Daniel Daza; Michael Cochez (CoRR, 2020)

DeepCOVIDExplainer: Explainable COVID-19 Predictions Based on Chest X-ray Images. - Md. Rezaul Karim 001; Till Döhmen; Dietrich Rebholz-Schuhmann; Stefan Decker; Michael Cochez; Oya Beyan (CoRR, 2020)

Structured query construction via knowledge graph embedding. - Ruijie Wang 003; Meng Wang 009; Jun Liu 002; Michael Cochez; Stefan Decker (Knowl. Inf. Syst., 2020)

Unsupervised Feature Selection for Efficient Exploration of High Dimensional Data. - Arnab Chakrabarti; Abhijeet Das; Michael Cochez; Christoph Quix (ADBIS, 2021)

Towards Easy Vocabulary Drafts with Neologism 2.0. - Johannes Lipp; Lars Christoph Gleim; Michael Cochez; Iraklis Dimitriadis; Hussain Ali; Daniel Hoppe Alvarez; Christoph Lange 002; Stefan Decker (ESWC (Satellite Events), 2021)

Complex Query Answering with Neural Link Predictors. - Erik Arakelyan; Daniel Daza; Pasquale Minervini; Michael Cochez (ICLR, 2021)

Inductive Entity Representations from Text via Link Prediction. - Daniel Daza; Michael Cochez; Paul Groth (WWW, 2021)

DeepKneeExplainer: Explainable Knee Osteoarthritis Diagnosis From Radiographs and Magnetic Resonance Imaging. - Md. Rezaul Karim 001; Jiao Jiao; Till Döhmen; Michael Cochez; Oya Beyan; Dietrich Rebholz-Schuhmann; Stefan Decker (IEEE Access, 2021)

Deep learning-based clustering approaches for bioinformatics. - Md. Rezaul Karim 001; Oya Beyan; Achille Zappa; Ivan G. Costa; Dietrich Rebholz-Schuhmann; Michael Cochez; Stefan Decker (Briefings Bioinform., 2021)

Secure Evaluation of Knowledge Graph Merging Gain. - Leandro Eichenberger; Michael Cochez; Benjamin Heitmann; Stefan Decker (CoRR, 2021)

Updating Embeddings for Dynamic Knowledge Graphs. - Christopher Wewer; Florian Lemmerich; Michael Cochez (CoRR, 2021)

Knowledge Graphs - Aidan Hogan; Eva Blomqvist; Michael Cochez; Claudia d'Amato; Gerard de Melo; Claudio Gutierrez 001; Sabrina Kirrane; José Emilio Labra Gayo; Roberto Navigli; Sebastian Neumaier; Axel-Cyrille Ngonga Ngomo; Axel Polleres; et al. (Morgan & Claypool Publishers, 2021)

Inductive WN18RR and FB15k-237. - Daniel Daza; Michael Cochez; Paul Groth (Zenodo, 2021)

Potential Energy to Improve Link Prediction With Relational Graph Neural Networks. - Simone Colombo 003; Dimitrios Alivanistos; Michael Cochez (AAAI Spring Symposium: MAKE, 2022)

SlotGAN: Detecting Mentions in Text via Adversarial Distant Learning. - Daniel Daza; Michael Cochez; Paul Groth (SPNLP@ACL, 2022)

Query Embedding on Hyper-Relational Knowledge Graphs. - Dimitrios Alivanistos; Max Berrendorf; Michael Cochez; Mikhail Galkin 001 (ICLR, 2022)

Complex Query Answering with Neural Link Predictors (Extended Abstract). - Pasquale Minervini; Erik Arakelyan; Daniel Daza; Michael Cochez (IJCAI, 2022)

Prompting as Probing: Using Language Models for Knowledge Base Construction. - Dimitrios Alivanistos; Selene Baez Santamaría; Michael Cochez; Jan-Christoph Kalo; Emile van Krieken; Thiviyan Thanapalasingam (LM-KBC@ISWC, 2022)

Scientific Item Recommendation Using a Citation Network. - Xu Wang 032; Frank van Harmelen; Michael Cochez; Zhisheng Huang (KSEM (2), 2022)

Hyperbolic Embedding Inference for Structured Multi-Label Prediction. - Bo Xiong; Michael Cochez; Mojtaba Nayyeri; Steffen Staab (NeurIPS, 2022)

Scaling R-GCN Training with Graph Summarization. - Alessandro Generale; Till Blume; Michael Cochez (WWW (Companion Volume), 2022)

A Machine With Human-Like Memory Systems. - Taewoon Kim 002; Michael Cochez; Vincent François-Lavet; Mark A. Neerincx; Piek Vossen (CoRR, 2022)

QAGCN: A Graph Convolutional Network-based Multi-Relation Question Answering System. - Ruijie Wang 003; Luca Rossetto; Michael Cochez; Abraham Bernstein (CoRR, 2022)

Explainable AI for Bioinformatics: Methods, Tools, and Applications. - Md. Rezaul Karim 001; Tanhim Islam; Oya Beyan; Christoph Lange 002; Michael Cochez; Dietrich Rebholz-Schuhmann; Stefan Decker (CoRR, 2022)

Knowledge Graphs. - Aidan Hogan; Eva Blomqvist; Michael Cochez; Claudia d'Amato; Gerard de Melo; Claudio Gutierrez 001; Sabrina Kirrane; José Emilio Labra Gayo; Roberto Navigli; Sebastian Neumaier; Axel-Cyrille Ngonga Ngomo; Axel Polleres; et al. (ACM Comput. Surv., 2022)

Towards a standard-based open data ecosystem: analysis of DCAT-AP use at national and European level. - Florian Barthélemy; Michael Cochez; Iraklis Dimitriadis; Naila Karim; Nikolaos Loutas; Ioannis Magnisalis; Lina Molinas Comet; Vassilios Peristeras; Brecht Wyns (Electron. Gov. an Int. J., 2022)

Editorial of the Special Issue on Deep Learning and Knowledge Graphs. - Mehwish Alam; Davide Buscaldi; Michael Cochez; Francesco Osborne; Diego Reforgiato Recupero; Harald Sack (Semantic Web, 2022)

Convolutional Embedded Networks for Population Scale Clustering and Bio-Ancestry Inferencing. - Md. Rezaul Karim 001; Michael Cochez; Achille Zappa; Ratnesh Sahay; Dietrich Rebholz-Schuhmann; Oya Beyan; Stefan Decker (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Bengali Hate Speech Detection Dataset. - Sumon Kanti Dey; Michael Cochez; Md. Rezaul Karim 001 (UCI Machine Learning Repository, 2022)

A Machine with Short-Term, Episodic, and Semantic Memory Systems. - Taewoon Kim 002; Michael Cochez; Vincent François-Lavet; Mark A. Neerincx; Piek Vossen (AAAI, 2023)

Reasoning beyond Triples: Recent Advances in Knowledge Graph Embeddings. - Bo Xiong; Mojtaba Nayyeri; Daniel Daza; Michael Cochez (CIKM, 2023)

The Graph-Massivizer Approach Toward a European Sustainable Data Center Digital Twin. - Martin Molan; Junaid Ahmed Khan; Andrea Bartolini; Roberta Turra; Giorgio Pedrazzi; Michael Cochez; Alexandru Iosup; Dumitru Roman; Joze M. Rozanec; Ana Lucia Varbanescu; Radu Prodan (COMPSAC, 2023)

Adapting Neural Link Predictors for Data-Efficient Complex Query Answering. - Erik Arakelyan; Pasquale Minervini; Daniel Daza; Michael Cochez; Isabelle Augenstein (NeurIPS, 2023)

Qualifier Recommendation for Wikidata. - Andrei Mihai Ducu; Michael Cochez (Wikidata@ISWC, 2023)

Graph-Scrutinizer: Towards Massive Graph Analytics and Reasoning. - Joze M. Rozanec; Michael Cochez; Ruud van Bakel; Brian Elvesæter; Dumitru Roman (ICPE (Companion), 2023)

Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases. - Hongyu Ren; Mikhail Galkin 001; Michael Cochez; Zhaocheng Zhu; Jure Leskovec (CoRR, 2023)

Geometric Relational Embeddings: A Survey. - Bo Xiong; Mojtaba Nayyeri; Ming Jin 005; Yunjie He; Michael Cochez; Shirui Pan; Steffen Staab (CoRR, 2023)

Approximate Answering of Graph Queries. - Michael Cochez; Dimitrios Alivanistos; Erik Arakelyan; Max Berrendorf; Daniel Daza; Mikhail Galkin 001; Pasquale Minervini; Mathias Niepert; Hongyu Ren (CoRR, 2023)

DONUT-hole: DONUT Sparsification by Harnessing Knowledge and Optimizing Learning Efficiency. - Azhar Shaikh; Michael Cochez; Denis Diachkov; Michiel de Rijcke; Sahar Yousefi (CoRR, 2023)

GNN2R: Weakly-Supervised Rationale-Providing Question Answering over Knowledge Graphs. - Ruijie Wang 003; Luca Rossetto; Michael Cochez; Abraham Bernstein (CoRR, 2023)

Knowledge Graph Embeddings: Open Challenges and Opportunities. - Russa Biswas; Lucie-Aimée Kaffee; Michael Cochez; Stefania Dumbrava; Theis E. Jendal; Matteo Lissandrini; Vanessa López; Eneldo Loza Mencía; Heiko Paulheim; Harald Sack; Edlira Vakaj; Gerard de Melo (TGDK, 2023)

Structural Summarization of Semantic Graphs Using Quotients. - Ansgar Scherp; David Richerby; Till Blume; Michael Cochez; Jannik Rau (TGDK, 2023)

Approximate Answering of Graph Queries. - Michael Cochez; Dimitrios Alivanistos; Erik Arakelyan; Max Berrendorf; Daniel Daza; Mikhail Galkin 001; Pasquale Minervini; Mathias Niepert; Hongyu Ren (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Explainable AI for Bioinformatics: Methods, Tools and Applications. - Md. Rezaul Karim 001; Tanhim Islam; Md Shajalal; Oya Beyan; Christoph Lange 002; Michael Cochez; Dietrich Rebholz-Schuhmann; Stefan Decker (Briefings Bioinform., 2023)

BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs. - Daniel Daza; Dimitrios Alivanistos; Payal Mitra; Thom Pijnenburg; Michael Cochez; Paul Groth (J. Biomed. Semant., 2023)

A knowledge graph approach to predict and interpret disease-causing gene interactions. - Alexandre Renaux; Chloé Terwagne; Michael Cochez; Ilaria Tiddi; Ann Nowé; Tom Lenaerts (BMC Bioinform., 2023)

QAGCN: Answering Multi-relation Questions via Single-Step Implicit Reasoning over Knowledge Graphs. - Ruijie Wang 003; Luca Rossetto; Michael Cochez; Abraham Bernstein (ESWC (1), 2024)

First International Workshop on Scaling Knowledge Graphs for Industry: Summary. - Michael Cochez; Evgeny Kharlamov; Radu Prodan (SEMANTiCS (Posters, Demos, Workshops & Tutorials), 2024)

Back to the Future: predicting causal relationships influencing oil prices. - Joze M. Rozanec; Beno Sircelj; Michael Cochez; Gregor Leban (Tiny Papers @ ICLR, 2024)

Workshop on Deep Learning and Large Language Models for Knowledge Graphs (DL4KG). - Mehwish Alam; Davide Buscaldi; Michael Cochez; Genet Asefa Gesese; Francesco Osborne; Diego Reforgiato Recupero (KDD, 2024)

UnRavL: A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs. - Tamara Cucumides; Daniel Daza; Pablo Barceló; Michael Cochez; Floris Geerts; Juan L. Reutter; Miguel Romero 001 (LoG, 2024)

The Effect of Knowledge Graph Schema on Classifying Future Research Suggestions. - Dimitrios Alivanistos; Seth van der Bijl; Michael Cochez; Frank van Harmelen (NSLP, 2024)

Explaining Graph Neural Networks for Node Similarity on Graphs. - Daniel Daza; Cuong Xuan Chu; Trung-Kien Tran; Daria Stepanova 001; Michael Cochez; Paul Groth (CoRR, 2024)

Leveraging Knowledge Graph-Based Human-Like Memory Systems to Solve Partially Observable Markov Decision Processes. - Taewoon Kim 002; Vincent François-Lavet; Michael Cochez (CoRR, 2024)

Do graph neural network states contain graph properties? - Tom Pelletreau-Duris; Ruud van Bakel; Michael Cochez (CoRR, 2024)

Neural Graph Reasoning: A Survey on Complex Logical Query Answering. - Hongyu Ren; Mikhail Galkin 001; Zhaocheng Zhu; Jure Leskovec; Michael Cochez (Trans. Mach. Learn. Res., 2024)

Code for Hyperbolic Embedding Inference for Structured Multi-Label Prediction. - Bo Xiong; Mojtaba Nayyeri; Michael Cochez; Steffen Staab (DaRUS, 2024)

Bias by Design: Diversity Quantification to Mitigate Structural Bias Effects in AIG Logic Optimization. - Isabella Venancia Gardner; Marcel Walter; Yukio Miyasaka; Robert Wille; Michael Cochez (DATE, 2025)

Interactive Query Answering on Knowledge Graphs with Soft Entity Constraints. - Daniel Daza; Alberto Bernardi; Luca Costabello; Christophe Guéret; Masoud Mansoury; Michael Cochez; Martijn Schut (CoRR, 2025)